基于重叠社区模型的多智能体一致性协议

    Overlapping Community Model-based Multi-agent Consensus Protocol

    • 摘要: 多智能体一致性问题是多智能体协同控制研究中的一个关键问题。传统的一致性研究未考虑到网络拓扑中的重叠结构,忽略了节点间连接的强弱程度,导致系统在演化过程中的弱连接更容易断开,影响系统一致性性能。基于社区网络中重叠节点能够促进不同社区信息互联的思想,提出了一种重叠社区模型(Overlapping Community Model,OCM) 。首先,提出分布式重叠节点发现算法(Distributed Overlapping Node Discovery Algorithm,DOND) ,用于识别系统中所有节点邻域范围的重叠节点。其次,提出了基于重叠度的拓扑权重设计算法(Overlap Degree-based Topology Reweighting Algorithm,ODTR) ,以量化节点之间的重叠程度从而动态分配权重。最后,提出了基于重叠社区模型的一致性协议。通过理论分析验证了该系统的稳定性,并对本文提出的一致性协议进行仿真实验,实验结果表明该协议能有效减少系统收敛簇数,从而增强系统一致性。

       

      Abstract: Consensus in multi-agent systems is a key problem in the research of multi-agent cooperative control. Traditional studies on consensus does not consider the overlapping structure in the network topology, neglecting the strength of connections between nodes, resulting in weaker connections being more prone to disconnection during system evolution, thereby affecting system consistency performance. Based on the idea that overlapping nodes in community networks can promote information interconnection between different communities, this paper proposed an Overlapping Community Model (OCM) . Firstly, this paper proposed a Distributed Overlapping Node Discovery Algorithm (DOND) algorithm, which can be used to identify overlapping nodes in all nodes' neighborhood in the system. Secondly, this paper proposed an Overlap Degree-based Topology Reweighting Algorithm (ODTR) algorithm to quantify the overlap degree between nodes and dynamically assign weights. Finally, this paper proposed an overlapping community model-based multi-agent consensus protocol. The stability of the system is verified by theoretical analysis, and the consensus protocol proposed in this paper is simulated. The experimental results show that the protocol can enhance the system consensus by reducing the number of convergence clusters.

       

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